MNIST Clock Uses Famous Training Database

When training neural networks to recognise things, what you need is a big pile of training data. You then need a subsequent pile of testing data to verify that the network is working as you’d expect. In the field of handwriting recognition, the MNIST database is commonly used to train networks on handwritten numerals. After [Evan Pu] mentioned it would be fun to use this data to create a clock, [Dheera Venkatraman] got down to work.

The original sketch which inspired the build.

The MNIST database contains 60,000 training images, and 10,000 test images. [Dheera] selected an ESP32 to run the project, which packs 4MB of flash storage – more than enough to store the testing database at 196 bytes per numeral. This also gives the project network connectivity, allowing the clock to use Network Time Protocol to stay synchronised – thus eliminating the need for an external RTC. Digits are displayed on four separate e-ink displays, which fits well with the hand-drawn aesthetic. It also means the clock doesn’t unduly light up the room at night.

It’s a fun project that will likely draw a knowing chuckle from those working in the field of handwriting recognition. We’d love to have one on our desk, too. If you’re thinking of attempting a build yourself, check out our recent contest for more inspiration!

Neural Network Does Your Homework

[Will Forfang] found a app that lets you take a picture of a math equation with a phone and ask for a solution. However, the app wouldn’t read handwritten equations, so [Will] decided to see how hard that would be, using a neural network.

The results are pretty impressive (you can also see the video below). [Will] used his own handwriting on a chalkboard and had the network train on that. He also went even further and added some heuristics to identify fraction bars and infer the grouping from the relative size of the bars.

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Ask Hackaday: DIY Handwriting Recognition

Computer handwriting recognition is very cool by itself, and it’s something that we’d like to incorporate into a project. So we went digging for hacker solutions, and along the way came up with an interesting bit of history and some great algorithms. We feel like we’ve got a good start on that front, but we’re stuck on the hardware tablet sensor itself. So in this Ask Hackaday, we’re going to make the case for why you could be using a tablet-like device for capturing user input or doing handwriting recognition, and then we’re going to ask if you know of any good DIY tablet designs to make it work.

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